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Probing depression, schizophrenia, and other psychiatric disorders using fNIRS and the verbal fluency test: A systematic review and meta-analysis

心理学 神经影像学 口语流利性测试 精神分裂症(面向对象编程) 精神科 荟萃分析 认知 重性抑郁障碍 临床心理学 萧条(经济学) 精神病 神经心理学 医学 经济 宏观经济学 内科学
作者
Michael K. Yeung,Jingxia Lin
出处
期刊:Journal of Psychiatric Research [Elsevier BV]
卷期号:140: 416-435 被引量:114
标识
DOI:10.1016/j.jpsychires.2021.06.015
摘要

Accessible neuroimaging tools that can identify specific frontal lobe dysfunction associated with psychiatric disorders could be useful for improving disease diagnosis and prognosis and treatment development. Functional near-infrared spectroscopy (fNIRS), in conjunction with the verbal fluency test (VFT), has emerged as an inexpensive and convenient method for understanding psychiatric disorders. However, questions remain regarding the specificity and uniqueness of fNIRS measurements for different disorders and the soundness of the methods applied previously. To address these knowledge gaps, we conducted a systematic review and meta-analysis of fNIRS studies using the VFT to probe psychiatric disorders. A literature search was conducted using PubMed and PsycINFO on October 27, 2020. Overall, 82% and 49% of the 121 included studies reported significantly reduced changes in oxyhemoglobin concentrations (HbO) and significantly fewer produced words during the VFT in psychiatric patients compared with healthy controls, respectively. For most psychiatric disorders, changes in HbO are more sensitive than changes in deoxyhemoglobin concentrations and VFT performance to detect psychopathologies. In addition, meta-analyses based on the proportion of channels that exhibited significant differences in HbO changes between patients and controls and on the effect sizes of group differences consistently showed that for major depression and schizophrenia, hypoactivation could be found across the frontotemporal regions, but its topographical distribution is disorder-specific. Thus, the fNIRS-VFT paradigm holds promise for understanding, detecting, and differentiating psychiatric disorders, and has the potential for developing accessible neuroimaging biomarkers for different psychiatric disorders. The findings are discussed with regard to the strengths and weaknesses of the applied methods, following by recommendations.
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